I guess you can get the result by
1) concatenating all the variables (P2_A, P2_B, P2_C) into one variable ,
2) replicating segment membership properly,
3) make the table of 1) and 2)

For example, the following may do the job.

> ## (1) Generate data set
> # Set random seed
> set.seed(0)
>
> n.obs <- 15 # Number of patients
> disease.lv  <- 1:10 ## different types of disease
> data1 <- as.data.frame(t(replicate(n.obs, sample(disease.lv, 3)))) #
Create data set
> ## Create segment membership
> segment <- sample(LETTERS[1:3], n.obs, replace=TRUE)
>
> cbind(data1, segment)
   V1 V2 V3 segment
1   9  3 10       B
2   6  9  2       C
3   9 10  6       A
4   7  1  2       B
5   2  7  4       C
6   8  5  6       C
7  10  4  7       B
8  10  2  6       C
9   2  3  4       B
10  1  4  7       A
11  4  5  9       A
12  5  2  7       A
13  7  8  1       A
14  8  4  7       B
15  7  8  5       B
>
>
> ## (2) Table
> infec.all <- unlist(data1) # Concatenate all variables into one variable
> segment.all <- rep(segment, ncol(data1)) # Replicate the segment
membership as necessary
> table(infec.all, segment.all)
         segment.all
infec.all A B C
       1  2 1 0
       2  1 2 3
       3  0 2 0
       4  2 3 1
       5  2 1 1
       6  1 0 3
       7  3 4 1
       8  1 2 1
       9  2 1 1
       10 1 2 1



On Nov 30, 2007 10:10 AM, Alejandro Rodríguez <rodrigueza@schwabe.com.mx>
wrote:

> Hello,  I'm new using R and developing tables.
>
> I have a problem in developing a table.  In a questionaire I made I ask
> this
> question "Please tell me the first three sympthoms caused by Respiratory
> tract infection you've caught this year", then the people answer three
> sympthoms, the first mention (Top of mind) is saved in a variable called
> "P2_A", the second mention in a variable called "P2_B" and the third
> mention
> in "P2_C".  Each answer is coded with numbers like this:
>
> 1 = Flu
> 2 = Cough
> 3 = Asthma
> ....
>
> 13 = Fever
>
> I've already done a K-cluster analysis and segmented my data base.  So my
> first task is to develop tables to develop tables of frequencies crossing
> Cluster vs. "P2_A" in order to know which are the top of mind products and
> their frequencies by cluster, then the second mention and third mention.
> I've used this instruction which worked well:
>
> > table(infec1,aglomera)
>      aglomera
> infec1   1   2   3   4
>    1  117  88  76  83
>    2   10  10   9   7
>    3   15  11  14  14
>    4    2   0   1   1
>    5    2   3   1   0
>    6    1   0   1   0
>    8    3   3   0   1
>    9    3   1   1   0
>    11   0   0   1   1
>
> Where "infec1" is a factor of "P2_A" and "aglomera" is a factor of the
> variable "Cluster" I made.  It worked well when I study them
> separately...however I would like to know the TOTAL mentions of each
> sympthom by cluster.  I've done this exercise in SPSS using the "Multiple
> Response" instruction first grouping my three variables (i.e. "P2_A",
> "P2_B"
> and "P2_C") into a variable called "sick" and cross tabulating it vs.
> QCL_1
> (my cluster variable) and it gave me the table I need in this way (showed
> at
> the bottom of this mail):
>
> How can I made a table like this in R???.  I've tried combining my
> variables
> in a matrix and using xtabs, ftable, table, structable and a lot of
> combination of them but I haven't had succed with any of them.
>
> Please help me with this issue, I don't want to keep using SPSS any more.
>
> Thanx in advance.
>
> P.D. Result from SPSS is shown below.
>
>
>
>                * * *  C R O S S T A B U L A T I O N  * * *
>
>   $SICK (group)  mr sick
> by QCL_1  Cluster Number of Case
>
>
>                       QCL_1
>
>                Count  I
>                       I                                      Row
>                       I                                     Total
>                       I     1  I     2  I     3  I     4  I
> $SICK          --------+--------+--------+--------+--------+
>                    1  I   130  I    97  I    83  I    89  I   399
>  Gripe, influenza, ca I        I        I        I        I  83.1
>                       +--------+--------+--------+--------+
>                    2  I    53  I    55  I    42  I    46  I   196
>  Tos de cualquier tip I        I        I        I        I  40.8
>                       +--------+--------+--------+--------+
>                    3  I    33  I    36  I    36  I    39  I   144
>  Dolor irritación     I        I        I        I        I  30.0
>                       +--------+--------+--------+--------+
>                    4  I     5  I     1  I     2  I     3  I    11
>  Bronquitis           I        I        I        I        I   2.3
>                       +--------+--------+--------+--------+
>                    5  I     5  I     4  I     1  I     0  I    10
>  Sinusitis            I        I        I        I        I   2.1
>                       +--------+--------+--------+--------+
>                    6  I     1  I     1  I     1  I     3  I     6
>  Rinitis              I        I        I        I        I   1.3
>                       +--------+--------+--------+--------+
>                    8  I     8  I     6  I     4  I     4  I    22
>  Amigdalitis          I        I        I        I        I   4.6
>                       +--------+--------+--------+--------+
>                    9  I     6  I     4  I     1  I     2  I    13
>  Faringitis           I        I        I        I        I   2.7
>                       +--------+--------+--------+--------+
>                   10  I     1  I     2  I     2  I     3  I     8
>  Laringitis           I        I        I        I        I   1.7
>                       +--------+--------+--------+--------+
>                   11  I     1  I     1  I     1  I     1  I     4
>  Neumonia             I        I        I        I        I    .8
>                       +--------+--------+--------+--------+
>                   13  I     0  I     0  I     1  I     0  I     1
>  Asma                 I        I        I        I        I    .2
>                       +--------+--------+--------+--------+
>               Column      153      116      104      107      480
>                Total     31.9     24.2     21.7     22.3    100.0
>
> Percents and totals based on respondents
>
> 480 valid cases;  0 missing cases
>
>
>
> Act. Calef Alejandro Rodríguez Cuevas
> Analista de mercado
>
> Laboratorios Farmasa S.A. de C.V.
> Schwabe Mexico, S.A. de C.V.
>
> Bufalo Nr. 27
> Col. del Valle 03100
> Mexico, D.F.
> Mexico
>
> Tel. 52 00 26 80
> email: rodrigueza@schwabe.com.mx
>
> www.schwabe.com.mx
> www.umckaloabo.com.mx
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
======================================
T.K. (Tae-kyun) Kim
Ph.D. student
Department of Marketing
Marshall School of Business
University of Southern California
======================================

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